System for gap in care alerts

ABSTRACT

A gap in care alert system and method includes a computer network which receives health insurance claims data. A database with medical treatment protocols for medical conditions is in electronic communication with one or more processors, the computer network, and an electronic storage device. The processor is configured to analyze said health insurance claims data to identify a triggering event for an insured patient, establish a date for a follow-up event based on a treatment protocol, and generate a gap in care alert if subsequently gathered health insurance claims data does not contain the follow-up event by said date. An alert delivery subsystem delivers said alert electronically to a receiver.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. nonprovisional applicationSer. No. 14/086,652 filed Nov. 21, 2013, which claims the benefit ofU.S. provisional patent application number 61/729,130 filed on Nov. 21,2012, the disclosures of all of which are hereby incorporated byreference as if fully restated herein.

FIELD OF THE INVENTION

The present invention relates to a system and method for analyzing thepotential for gaps in patient care and providing alerts to patientsand/or care providers that a gap in care may arise or may have arisen sothat actions can be taken before a negative result occurs.

BACKGROUND AND SUMMARY OF THE INVENTION

The health care profession has known that gaps in patient care can leadto worsening health for the patient, and if that occurs there is thepotential for much higher costs of health care for the patient. Forexample, it is known that if a diabetic patient does not follow medicaladvice with respect to insulin treatment schedules the patient's healthmay deteriorate. It is also known that if a patient has had surgery anda scheduled follow up visit to the doctor is missed the patient'srecovery from surgery may be endangered which may result in the patienthaving to be readmitted to the hospital. Yet another example is in thearea of pharmacies. Patients given renewable prescriptions who fail torenew the prescription for a needed drug may result in the patient'scondition worsening.

All of the above scenarios are generally defined as gaps in care. Thereare many reasons why patients may have gaps in care, ranging fromforgetfulness, a life changing event, financial reasons, not taking thecare instructions seriously, etc. Whatever the reason may be it isimportant to alert the patient or other entity concerned with thepatient (such as their healthcare provider) of a possible gap in care.Systems and methods have been used to alert various entities of medicalinformation important to convey. For example, U.S. Pat. No. 5,754,111shows one such system. Systems have been developed that use knownmedical data about a patient compared to historically collected medicaldata about drugs, conditions, interactions, contraindications, etc., toimprove care for the patient. U.S. Pat. No. 7,809,585 describes such asystem and method. The entireties of both of these patents are herebyincorporated by reference herein.

The danger in having a gap in care is that the failure to follow medicalinstructions can result in undesirable outcomes for the patient. Theseundesirable outcomes may include a slower recovery, a complete lack ofrecovery potentially resulting in a chronic condition that could havebeen avoided, or in some cases, a dangerous worsening of a patient'scondition. These results are undesirable for the patient's health butalso often result in increased health care costs. Incomplete health carecan lead to inefficiencies in care. The public, the news media, and somegovernment agencies have become increasingly concerned about the costand quality of health care. One set of factors that have been applied tomeasure the quality of care provided is the Healthcare EffectivenessData and Information Set (HEDIS). HEDIS was developed by the NationalCommittee for Quality Assurance. In addition to the general increase inpublic awareness of medical care cost and quality, the HEDIS factorsprovide additional incentive for medical service and health insuranceproviders to work to control costs and improve patient care. In additionto HEDIS, the Centers for Medicare and Medicaid Services (CMS) havedeployed an additional rating system known as “STAR.”

In addition to helping to ensure that the performance in the areasconsidered by HEDIS and STAR are optimized, solutions that minimize theimpact of gaps in care have the beneficial effects of improving thequality of care provided to patients, keeping patients healthy orimproving their health, and reducing the cost of medical care.

Today's existing computer technologies allow the gathering and analysisof medical data of a patient's medical history. Today, a patient'smedical records are often stored electronically, sometimes in records orfiles known as electronic medical records or EMRs. EMRs are well knownsuch that details of their formation, updating, storing, sending, andreceiving electronically via computer network are not explained herein.This electronic storage provides a repository of patient careinformation that can be leveraged by the health care system to improve apatient's care and reduce the overall cost of a patient's medicaltreatment. Methods of leveraging a patient's medical record(s) to reducegaps in care have been developed but can fall short in their ability tochange the behavior of patients when it comes to avoiding gaps in care.

The present invention resides in improvements to the means fordeveloping, generating, and communicating the potential for or theexistence of a gap in care for a patient. This is done in such a way asto encourage a change in the patient's behavior sufficiently to causethe patient to take the actions required to eliminate or prevent the gapin care. This communication is also delivered in a manner calculated tominimize the actual time of gap in care or prevent a gap in care fromhappening in the first place. It is understood that once a gap in careapproaches or begins, a lengthy delay in communication may widen thetime of a gap in care and in doing so, increase the likelihood of anunfavorable impact on the patient or increase the cost of care requiredto make the patient well.

Various known means of communication may be useful with the presentinvention. For example, outbound automated phone dialers in electroniccommunication with a computer system (such as used by telemarketingcompanies) may be useful in phoning someone about a gap in care. Knowncomputer automated email servers or texting services may also be used tocontact someone about a gap in care. Connected to a computer system thatdetermines when to issue an alert or to send an alert, such knownsystems can be useful in delivering the alert.

In an exemplary embodiment of the present invention, a computer systemanalyzing patient medical data detects an approaching potential for gapin care and initiates the generation of an alert message and delivery ofa communication containing the message directly to the patient in theform of an automated phone call. A communication directly to the patientserves as an efficient and cost effective method to inform and encourageaction to eliminate the gap in care. In another exemplary embodiment ofthe invention, such a phone call is made to a home health care servicewhich then may attempt to contact the patient by an in-person visit tothe patient's residence in order to check on the patient's condition andfurther encourage the patient to conform to the care recommendationsprovided by their health care provider. Other means for delivering thealerts will be described in the following detailed description, as willmeans for generating an alert.

In addition to the novel features and advantages mentioned above, otherbenefits will be readily apparent from the following descriptions of thedrawings and exemplary embodiments.

BRIEF DESCRIPTIONS OF THE DRAWINGS

While the appended claims set forth the features of the presentinvention with particularity, the invention and its advantages may beunderstood from the following detailed description taken in conjunctionwith the accompanying drawings, wherein identical parts are identifiedby identical reference numbers and wherein:

FIG. 1 shows a diagrammatic view of a computer network for use with thepresent invention;

FIG. 2 shows a diagrammatic view of delivery mechanisms for the alertsof the present invention;

FIG. 3 shows a flow chart of the algorithm of a preferred embodiment ofthe present invention;

FIGS. 4A and 4B show a flow chart of the gap in care detection algorithmfor a preferred embodiment of the present invention;

FIGS. 5A and 5B show a flow chart of the follow-up care gap in caredetection algorithm for a preferred embodiment of the present invention;

FIG. 6 shows a flow chart of the protocol analysis algorithm of apreferred embodiment of the present invention;

FIG. 7 shows a flow chart of the time to alert algorithm of a preferredembodiment of the present invention; and

FIG. 8 shows a flow chart of an example process of the present inventionfor calculating the time threshold that indicates a potential gap incare.

DETAILED DESCRIPTION OF THE INVENTION

The health care system comprises the interactions of three key entities;health care consumers (patients), health care providers, and healthinsurance providers. When a patient becomes ill, they visit theirprimary care physician if they have one. If not, a patient may visit anurgent care facility, emergency room, or as is becoming more common, anurse practitioner that may have an office located in a grocery or drugstore. The fact that a patient may visit any one of these health careproviders creates the potential for a multiplicity of medical recordlocations. In such a three entity system, health insurance providers arein a unique position in that they are the recipient, in the form ofclaims data, of a comprehensive medical record for those health careconsumers (patients) that obtain their health care insurance from thehealth care provider (referred to as members).

When the patient visits a health care provider, they may receive adiagnosis, a recommended treatment protocol and possibly a prescriptionfor medication. Depending on the disease or condition diagnosed, thehealth care provider may prescribe one or more medications. If thedisease or condition requires additional treatment, the treatmentprotocol may require follow-up care.

With reference to FIG. 1 after visiting a health care provider 32, theprovider and/or the patient may submit a claim 15 for insurance paymentor reimbursement to the patient's health insurance provider 19, forexample, via a computer network 14. That claim may contain details ofthe diagnosis and care provided, along with prescriptions written.

After meeting with the health care provider in a case where aprescription for a drug is written for the patient, the patient may filla prescription at a pharmacy 30. The pharmacy and/or the patient maygenerate a claim 15 or report to the patient's health insurance provider19. This claim may contain information including, for example,identifying information about the patient, the health care provider thatgenerated the prescription, the drug prescribed, the quantity given, andthe remaining refills available.

In addition to the patient's primary care physician there are otherentities that may be providers of health care to a patient. These mayinclude hospitals, medical specialists, physical therapists, home healthcare assistants 31, and many other types of care providers. When theseadditional health care providers perform a health care service for apatient, that provider 31 and/or the patient 33 may submit a claim 15 tothe patient's health insurance provider 19 to obtain payment for theservices provided. This insurance claim may contain data sufficient todetermine a recommended treatment protocol and prescribed follow-upcare.

The commonality in each of the previous scenarios is that claims fromhealth care providers are submitted to the patient's health insuranceprovider. At the health insurance provider, the claim information may beused to process the patient's medical claims and provide payments to therespective service providers according to the terms of the healthinsurance agreement between the patient and the health insuranceprovider. This agreement allows the health insurance provider todetermine what benefits the patient is entitled to and whether thehealth care provider is following generally accepted methods oftreatment for particular medical conditions.

When a claim is submitted, the patient's claims become part of his orher health record 17 maintained by the health insurance provider on itscomputer network 19. Because this health record persists after apatient's claims have been paid, the health record serves to gather andmaintain information taken from claims submitted by a patient while heor she is served by the health insurance provider. The result is anaccumulation of data concerning the patient which may comprise pastillnesses, personal data such as age, sex, and ethnicity, vaccineschedules, drugs prescribed, harmful drug reaction, allergies, andfamily medical history as provided by the patient.

The sheer volume of data and number of patients supported by a healthinsurance provider requires that in order to perform even the basicfunction of processing and paying claims that the data be managed by asophisticated computer system 10 having one or more processors 12 anddatabases 16. Exposure to a computer system 10 allows the data to besubject to various forms of analysis. One such type of analysis servesas a means to detect gaps in care 20 (see for example, FIG. 3).

In some cases, failure to follow a recommended care regimen may resultin a patient not recovering as quickly, suffering from additionalillness or disease, or, developing potentially life-threateningcomplications. For the patient, health care providers, and society, acontinued or worsening illness results in frustration, loss of enjoymentof life, potential injury, and when taken in the aggregate, an impact onthe productivity of the economy as a whole. A follow-up visit to aprimary physician, the resulting prescription cost, and follow-up carecosts are just a fraction of what a prolonged recovery or more seriousillness may cost in terms of an extended hospital stay that may resultif the patient does not follow a prescribed treatment regimen. There isa need for means for prompting the patient to follow a recommendedtreatment protocol to avoid a situation in which a relatively minordisease progresses to something much more severe, and more costly totreat.

There may be many reasons why a patient does not follow a prescribedtreatment regimen. A patient may feel that they are too busy to wait ina health care provider's office for an appointment. A patient may decidethat he or she seems to feel better and therefore avoid scheduling afollow-up visit or refilling a prescription to save money. A patient maysimply be forgetful or have a medical condition that makes it hard forthem to remember and follow instructions. If someone can communicate thepotential problems that may result should the patient fail to follow theprescribed treatment protocol, that patient may realize the benefit offollow-up and proceed with their prescribed care. A gap in care systemas described herein may provide the information needed to communicatethe need for resumption of prescribed care.

With reference to FIG. 3, a gap in care system 20 of the presentinvention may be implemented by analyzing a patient's medical treatment21 and other data in the patient's record, which may be obtained frominsurance claims data 15 received at the health insurance companycomputer network 19. The computerized system automatically identifiesupcoming action dates 22, which indicate that a patient is approaching acare event, which if not completed will result in a gap in care 24. Forexample, using a look-up table of identified and generally acceptedvaccination schedules, the system can identify when the patient's lastvaccine (if any) was administered and from comparing that to thegenerally accepted vaccination data in a look-up table forming a part ofthe computer system 10 the system determines a due date for the nextvaccination for that patient. At a predetermined time (which may beselected by the user and input into the system) prior to the due datethe system automatically generates an alert to warn the patient of theneed to take action and sends it out over the alert delivery subsystem18 to a patient or someone in connection with the patient. Likewise,numerous other patient care actions may be analyzed and calculated bythe system of the present invention. For example, the need for aprecautionary colonoscopy by age fifty may be the subject of an alertmessage to adults of age forty-nine. As another example, an alertadvising of the need for an annual wellness physical may be sent eachyear after a patient's fortieth birthday. Aside from widely implementedcare actions (such as vaccines) taken by a large portion of thepopulation, more particular actions of care may be identified on apatient by patient basis from data particular to each patient, stored inthe record for each patient in the computer of the system of the presentinvention. For example, if data on a particular patient indicates ahistory of high blood pressure, the system of the present invention maybe used to alert the patient periodically to the need to have theirblood pressure checked. The process of the present invention determinesa particular care action date for a patient after which if thatparticular care is not obtained by the patient an actual gap in careexists; then alerts the patient in advance of the care action date toseek the particular care identified in the alert, and thereby avoid agap in care.

For the purposes of gap in care analysis and alerts, a health insuranceprovider is in a unique position. Unlike any single health serviceprovider or primary care physician, the health insurance provider hasaccess to an aggregate of the patient's medical history acrosspractically all forms of health care and sources of that care. Forexample, a primary care physician may not have a complete record of apatient's care if that patient were to see a health care provider whileon vacation in another city or state and that second health careprovider failed to deliver a record of the visit or diagnosis to thepatient's primary care physician. Another example might be a situationin which a patient provided the incorrect or incomplete name of hisprimary care physician when visiting an emergency room. Because apatient and/or care provider will very likely seek insurance coverage inevery instance of care, the health insurance provider may have the mostcomplete record of a patient's history.

With reference to FIGS. 5A and 5B, to implement a computerized gap incare detection system, claims data received and stored 41 in the recordfor a particular patient may be analyzed 42 with regard to the type oftreatment received, the disease or condition diagnosed, prescription(s)written, and/or the treatment protocol recommended to the patient at 44.A computer algorithm may first check the patient record for arecommended treatment protocol by the health care provider for which theclaim was submitted. This may result in the detection of a recorddetailing recommend follow-up visit(s), prescription medicationrequirements, or other direction to the patient from the health careprovider along with a determined date by which such activity(ies) shouldoccur 52. By subtracting a number of days from the determined date, anotice date is defined at 53. The number of days subtracted may beselected by a user of the system entering the number of days into theprogram that the user believes is best suited for an early warning of anapproaching gap in care. Alternatively, the program may be preset tosubtract a particular number of days from the determined date per givendiagnosis. Once the notice date arrives, an early warning gap in carealert is generated at 55 and an alert is delivered.

The system may continue to check for whether any follow-up actions havenot yet been completed at 59. If so the processor determines whether thedate has passed by which a follow-up action was to have occurred, at 56,by reviewing more recently received insurance claims data for thepatient. If the patient records show that the patient completed thefollow-up action, at 58, the action is noted as being completed in thepatient record. If records indicate the patient has not completed thefollow-up action a gap in care alert may be generated, at 54. In oneembodiment the system surveys for any other follow-up actions thepatient has due, and consolidates the communications in a single alert.

Referring to FIG. 6, a comparison 61 may then be conducted during whichhealth care provider recommendations may be compared to a benchmark setof recommended treatment protocols for the type of illness, condition,or disease diagnosed. Such benchmark protocols may be acquired from arecognized source of such data or may be derived internally by a healthinsurance provider reviewing historical data for its insured patientsover a lengthy period of time. Discrepancies between the results ofthese analyses may be reviewed by an exception process 62 and revised 68if necessary to be consistent with established standards. Once thetreatment protocol prescribed by the health care provider is checked tosee if it is in conformance with the standards for that diagnosis, at 64it may be analyzed and stored, if not a message may be generated 66 tothe health care provider to alert them to the results of the comparison.

Accordingly, a set of follow-up care requirements may then beestablished for insured patient claims. Patient follow-up requirementsdiffer depending upon what type of action is required. A first categorycomprises return visits to the health care provider that performed theinitial diagnosis. A gap in care may be indicated if the patient failsto return within an anticipated date for follow up. A second category isthat of prescription drugs. FIGS. 4A and 4B show a flow diagram of thecomputer program algorithm of the present invention for detecting gapsin care caused by a failure to fill drug prescriptions. An insuranceclaim for a patient is entered 19 into the system and may be sorted bydiagnosis code 42. A prescribed medication for the diagnosis may beidentified 44. A gap in care alert 54 may be indicated if either of thefollowing conditions is true: a drug has been prescribed to a patientand that patient has not filled the prescription within a calculatedtime 46 of the drug being prescribed; or a drug has been prescribed witha number of refills and the patient has not refilled the prescription 48as directed within a time after a refill period 49 as elapsed.

When implementing a gap in care detection system using medical insuranceclaims, an algorithm may be used to determine what time period elapsedbefore the gap in care detection system detects that there has been agap in care. Such an algorithm may be implemented by establishingpredetermined periods of time for each type of treatment protocol duringwhich the gap in care detection system will not indicate a gap in care.For example, if a treatment protocol indicates a follow-up action in twoweeks the algorithm may be programmed to wait the two weeks plus apredetermined period of days before generating an alert.

With reference to FIG. 7 there is shown a flow diagram of a computerprogram 74 which automatically calculates an optimized date for followup care and subtracted therefrom would be a number of days (e.g., 14days) and from the resulting date an alert would be generated and sentautomatically to advise the patient in advance of the potential for agap in care. Such time periods for which a gap in care warning ornotification or alert is indicated may be assigned to any triggeringevent 70. These periods may be calculated based upon analysis ofmultiple factors, which may comprise the disease, ailment, or surgerysuffered by the patient, the treatment protocols prescribed,characteristics and demographics of the patient, statistical analysis ofthe time generally required to file a particular type of claim, and thehistorical behavior of the current patient or health care provider withregard to submitting health insurance claims.

A triggering event which starts the clock of the present invention mayinclude but is not limited to, a date of surgery, a date of diagnosis ofa disease, a date of treatment beginning, a date an initial prescriptionfor medication is filled, a date of a doctor's office visit by apatient, or practically any other identifiable date from which asubsequent follow up activity should occur. By identifying the specificnature of the triggering event using codes for treatment/diagnosisprovided by the health care provider, the processor 12 may access adatabase of medical treatment protocols 16 to determine the nextscheduled follow up event for that triggering event and posts thatfollow up event date in the computer record associated with the patient.Warnings/alerts may be automatically sent by the system 10 to thepatient at a predetermined time in advance of the next scheduled followup event as a reminder to the patient to avoid a gap in care.

When a triggering event occurs for a patient 70, the processor 12 mayperform a comparison 71 based on then-current data, including that dataspecific to the patient, the patient's disease, ailment, or surgery, andthe prescribed treatment protocol applied to the patient's care, in viewof generally accepted treatment protocols.

Once a threshold care/triggering event has been determined, thealgorithm is then implemented to monitor patient data in the form ofclaims submitted for follow-up prescriptions and/or care services. Forexample, a triggering event occurs for a patient (such as kneereplacement surgery) on a particular date. An insurance claim is filedfor the patient and the health insurance company enters the data fromthe claim into a computer network. The gap in care detection algorithmof the present invention stores the triggering event in a fileassociated with the patient's id, for future reference pertaining tofollow-up event(s). Next, the present invention preferably automaticallydetermines when a follow-up event should occur for the patient 72, basedon, for example, a look-up table of particular health care triggeringevents (e.g., knee replacement surgery) and time period(s) whenassociated recommended treatment protocol follow-up events (e.g.,follow-up “post-op” visit with the surgeon) should occur (e.g., fourteendays after the surgery date), based on generally accepted medicalprotocols. The present invention then stores the recommended follow-upevent and recommended follow-up event date in the computer network 19,associated with the patient's id. In a preferred embodiment the presentinvention alerts the patient days in advance 75 of the follow-up eventto avoid a gap in care. The present invention preferably includes aclock associated with the computer network that automatically sets afollow-up event date (minus an early warning period) 72 for eachtriggering event and then tracks that follow-up event date to see if aninsurance claim is received for the follow-up event by that date.

Future submitted health insurance claims data may indicate that thepatient accomplished the follow up event. If the anticipated date forthe follow up event passes and a grace period (or none) passes withoutreceiving an additional claim for that follow up event, the system ofthe present invention recognizes that there has been a gap in care. Oncethe system identifies the gap in care an alert signal is actuatedautomatically by the system and the delivery of the alert is handledautomatically by the alert delivery subsystem 18 of the presentinvention.

Gap in care alerts may be generated by the present invention in advanceof and as an early warning to the patient or care provider of anapproaching gap in care, or as a notice that an actual gap in care hasalready occurred. Such alerts may be delivered via an alert deliverysubsystem of the present invention, as shown in FIG. 2. The alertdelivery subsystem 18 may be configured to deliver the alerts direct topatient devices 33 (e.g., phones, mobile computing devices, homecomputers, etc.) or to other entities 30, 31, 32, 36 on behalf of thepatient (e.g., a health care provider device). The delivery subsystemmay use various forms of communications to deliver the alerts (e.g.,voice message, text message, email message, warning message to an EMR36, etc.). The alert message itself may take many forms, including butnot limited to: a simple direct informational message that a particularpatient follow-up event is upcoming and reminding the patient or healthcare provider that the patient should perform the follow-up event soon;a robust message describing a particular gap in care and the potentialdangers of not accomplishing the follow-up event and a reminder to doso; or a short message indicating that the patient is requested tocontact their health care provider or health insurance companyrepresentative about an important message for them.

Two examples may be helpful to illustrate the process. In a firstexample, a claim is submitted that details a follow-up requirementcalling for a return visit to the diagnosing physician. The follow-upperiod is combined with a calculated early warning period. The existenceof the requirement for a return visit triggers the gap in care warningalgorithm. The algorithm then monitors for claims submitted by or onbehalf of the patient for a return visit to the physician. If aninsurance claim is not submitted within the calculated time, a potentialgap in care may have occurred and is thereby detected. In a secondexample, a prescription is given to the patient that includes threerefills, each with a thirty-day refill period. The claim that containsthe record of this prescription triggers the gap in care algorithm. Thealgorithm monitors the patient's claim data to determine if each refillis done within the refill period plus a grace period. The grace periodmay be for example about five days on top of the original refill date toallow the patient to visit a pharmacy to obtain a refill. For purposesof this example, if the prescription is not refilled within five daysafter the refill period, a potential gap in care may exist. As with thefirst example, the indication that the patient has taken an action inresponse to a prescribed treatment protocol (refilling a prescription inthis example), is the result of a claim to the health insuranceprovider.

The lack of a claim is an indication that a patient may not havefollowed a prescribed treatment protocol. The gap in care detectionalgorithm therefore consists of a means for analyzing patient claimsdata to detect claims that contain prescribed treatment protocols(sparking a triggering event). When such a claim is detected, thealgorithm stores a record of follow-up requirements and calculatedcompletion times associated with the prescribed treatment protocol for agiven patient. The system of the present invention then alerts or warnsthe patient in advance of an approaching gap in care to seek theparticular treatment by a particular date or within a particulartimeframe. The algorithm then monitors that patient's claims submittedfor indications that each of these follow-up requirements has beensatisfied. As each requirement is satisfied, the algorithm may remove itfrom the record of follow-up requirements. If the algorithm determinesthat a requirement remains in the record of follow-up requirement beyondthe expected completion time, an alert may be generated for furtheraction.

The gap in care detection algorithm and analysis process for monitoringclaims data are preferably but not necessarily performed on a processorsystem maintained by the health insurance provider 10. This processorsystem is connected via a network 19 that houses patient claim data.Various other computer systems may be equipped to access the networkincluding a system for entering claims data 14 into the network, forexample over the internet. This claim data entry system may beimplemented in a number of traditional ways.

Once the gap in care algorithm identifies a potential gap in care for apatient, the algorithm triggers an alert or early warning. This alertmay trigger a further review process at the health insurance provider oralternatively at the health care provider associated with the claim andof the lack of follow-up that caused the gap in care detection algorithmto generate the alert. Once any review is completed, the gap in careearly warning may be communicated to an individual or organization by analert delivery subsystem 18 to follow up with the health care provideror patient. An improvement in gap in care detection comprises acomputerized notification system which may be maintained in associationwith the health insurance provider and connected to the computer networkand database which contains patient records and the results of the gapin care detection algorithm's analysis. Referring to FIG. 2, thisnotification system may be connected to an automated telephone system 29which when activated by the subsystem 18 generates phone calls to notifypatients that a potential gap in care is about to occur or has beendetected. This notification system may also include a computerizedmessaging system 13 capable of sending emails, text messages, or othermeans of electronic messaging, such means being a rapidly expandingtechnology such that a person skilled in the art will realize additionalpossibilities for messaging.

Referring to FIG. 1, health insurance claims data 15 is received by thehealth insurance computer system 10 and identifies recent medical careprovided for a particular patient. If needed or if desired, the computersystem may consult medical treatment protocol database 16 to determinethe subsequent steps in the treatment of the patient's condition,diseases, ailment, or surgery. The computer system may then determinethe next anticipated date for a follow up care event by the patient.Alternative sources may be used for completing the database 16. Forexample, commercially available treatment protocols may be used, thehealthcare provider's treatment protocol may be used, or an in-housegenerated treatment protocol may be used. Insurance companies areparticularly well situated with years of patient healthcare data to knowtreatment protocols that work well and ones that don't. To help preventgaps in care the system of the present invention automatically generatesan early warning alert to the patient or someone connected in some wayto the patient, informing the patient or connected person that anupcoming treatment or care action is needed or suggested by a particulardate or within a particular timeframe. The alert message preferablyincludes a brief description of an action to be taken to avoid a gap incare. If the date passes without follow up by the patient apredetermined grace period may be invoked by the system. After thepredetermined grace period, if any, and still no follow up by thepatient, the system of the present invention automatically generates analert. Once an alert is generated the computer system invokes the alertdelivery subsystem 18 to get the alert to its proper destination.

The alert, once provided to the alert delivery subsystem 18, may bedelivered over various channels to predetermined destinations. Forexample, the alert may be sent to a billing system 34 within theinsurance company for placement of an alert message on a premium invoice37 normally sent to an insured via regular mail or email. Or the alertmay be sent automatically through an email server to a destination emailserver for alerting a predetermined party of the gap in care via anemail message. The alert may be delivered to an electronic medicalrecord (EMR) 36 housed at a health care provider computer system andpresented as a written warning near the top of the EMR to be seen byhealth care professionals and/or a patient. Many methods of delivery ofthe alert are contemplated by the present invention.

The data used by the health insurance company computer system todetermine a gap in care alert may be derived from health insuranceclaims data, or various other sources, including health care providerdata received from heath care provider data systems, patient entereddata received directly from the patients/insureds, or from practicallyany other medical data source, including pharmacies, home health carefacilities, etc. The actual alerts generated by the system of thepresent invention may be in the form of printed words on paper,electronic words in electronic environment such as electronic messagesor texts, voice message, or even speech provided from a delivery persondirect to the patient or care provider.

In certain embodiments of the invention, a method of detecting gaps incare may be performed by calculating gap in care alert thresholds usingselected HEDIS and STAR performance measure rules. An exemplary list ofHEDIS and STAR rules is show in Appendix 1 included in this application.In addition to these rules, Appendix 1 also includes a discussion of howsuch rules may be used to calculate a failure date. In certainembodiments of the invention, this failure date may be used to indicatewhen a gap in care may occur and provide an alert in advance of thisdate.

In another embodiment of the invention, a triggering event may beidentified using a HEDIS or STAR category. An exemplary triggering eventmay be a patient reaching 50 years of age. HEDIS performance measurerules indicate that a patient should have colorectal cancer screeningprocedures starting at age 50 and continuing until age 75. Using thismethod, if that patient has not had colorectal cancer screening examupon turning 50 years of age, a gap in care may be generated. Inaddition, if such an exam has been conducted, the method may detect theoccurrence or occurrences of such exams and calculate the latestrecommended repeat of such exams. This latest date may be used to set athreshold, beyond which a gap in care may be indicated. An exemplaryalgorithm of such a method is illustrated in the flow chart of FIG. 8.In step 802 the algorithm determines if the patient is eligible for oneof the applicable HEDIS and STAR rules. Using the example previouslygiven, eligibility may be related to a patient reaching a certain age orage range. If the patient is not eligible based on the appropriateeligibility requirements, in step 804 the algorithm determines if thepatient will be eligible before the algorithm is run again in thefuture. If not, there is no applicable threshold and no gap in carewould be detected for the HEDIS or STAR rule being analyzed by thealgorithm. If step 804 determines that the patient will be eligiblebefore the next run of the algorithm, step 804 assumes that the patientis eligible and performs step 806. If in step 802 the patient isdetermined to be eligible, the algorithm continues with step 806. Instep 806 the algorithm determines if the patient has a condition thattriggers the rule. Using the previous example, a condition may be that apatient has had prior colorectal cancer screening procedures performed.Certain patients that may satisfy eligibility requirements in step 802may not have any related conditions that trigger a possible gap in care.In such a situation, the algorithm executes step 808 and indicates thatthere is no applicable threshold and no gap in care would be detectedfor the HEDIS or STAR rule being analyzed by the algorithm.

Once the algorithm illustrated in FIG. 8 has determined that a patienthas a condition that may trigger the applicability of a HEDIS or STARrule, step 810 identifies the condition or conditions. Step 812 usesHEDIS or STAR rule data to calculate the appropriate follow-up timeperiod for each condition. Using such rule data insures that timeperiods are identified that comply with HEDIS and STAR requirements. Instep 814 the follow up time periods are added to the dates correspondingto the conditions to which the time periods apply. The result may be alist of conditions and applicable follow up dates. In step 816 thealgorithm determines the latest date from those dates derived in step814. In certain situations a patient may no longer be eligible for theanalyzed HEDIS or STAR rule when the latest date is reached. An examplemay be a colorectal screening requirement that is only applicable untilage 75. In such an example, if the patient were to exceed 75 years ofage before the identified date, step 818 would indicate that there is noapplicable threshold and no gap in care would be detected for the HEDISor STAR rule being analyzed by the algorithm. If the patient isdetermined to still be eligible at the latest follow up date, step 820identifies applicable gap in care threshold as the latest follow up dateas identified in step 816.

The present invention has been described herein with reference to thefigures and various preferred embodiments, but is not to be construed aslimited thereto. The invention is susceptible to modifications andvariations that fall within the following claims. The claims of thepresent invention are not limited to the embodiments described in detailherein but are intended to have broad scope to capture the full scope ofthe present invention as allowed by law.

Appendix 1

What follows is a description of an example alert in advance of afailure date (or date at which a gap in care occurs):

The National Committee for Quality Assurance has developed a set offactors commonly referred to as the Healthcare Effectiveness Data andInformation Set (HEDIS). In addition to HEDIS, the Centers for Medicareand Medicaid Services (CMS) have deployed an additional rating systemknown as “STAR.” Selected HEDIS and STAR performance measure rules maybe used to calculate an expected time period between a triggering eventand the completion of an expected follow up event. Modifications may bemade to known, selected Healthcare Effectiveness Data and InformationSet (“HEDIS”) performance measures rules to compute the Failure Date asdefined in each rule. Logic to compute Failure Date may be incorporatedinto selected STAR Measure rules.

The following logic matrix defines when eligibility and categoryconditions may trigger the calculation of Failure Date:

Compliant Non-Compliant a. Now a. Now Interested in Failure b. By End ofb. By End of Date (FD)? Measurement Year Measurement Year Eligible forRule (today) a. Yes a. No b. No b. Yes Not Eligible For Rule a. N/A a.N/A (today) b. No b. YesIn order to illustrate how the Failure Date is calculated, a number ofscenarios are presented using the Colorectal Cancer Screening rule as anexample. This rule targets adults aged 50-75 years of age, anddetermines compliance based on the presence of one of 3 different tests.The rule defines the insurance coverage history required for the memberto be considered for the rule. These requirements are summarized below.

Denominator Numerator 49 > Age < 76 One of: FOBT in the past 12 monthsContinuous enrollment in the measurement sigmoidoscopy in past 5 yearsyear and the year prior, with no more than 1 gap of less than 46 days inthe measurement year or previous year. colonoscopy in past 10 years

Use Case 1:

Member is currently eligible, and compliant with the rule.Check 1—Will the member still be eligible by the end of the measurementyear? (If they will they turn 76 by the end of the measurement year,then no Failure Date will be calculated.)Check 2—Look for the LATEST service date of EACH of the tests whichwould satisfy the numerator, and add the appropriate test frequency. TheFailure Date would be the latest of these dates. For example, if amember had an FOBT 11 months ago, and a colonoscopy 4 years ago, theFailure Date would be the 10^(th) anniversary of the date of theColonoscopy.

Use Case 2:

Check to see if the member's age is within one year of the required age,i.e. is the member currently aged 49? Will the member meet the agerequirement by the end of the measurement year? If yes, note the datethe member will meet the ‘age-in’ requirement.Check to see if the member will meet the Coverage requirement by the endof the measurement year. If yes, note the date the member will meet the‘coverage eligibility’ requirement.If the member will be eligible before the end of the measurement year,look for the LATEST service date of EACH of the tests which wouldsatisfy the numerator, and add the appropriate test frequency. TheFailure Date would be the latest of these dates and the age-in andcoverage-in dates above.For example, if a member had never received any colorectal cancerscreening, had been continuously eligible for 2 years, and will turn 50between now and the end of the measurement year, the Failure Date is thedate the member turns 50.

-   -   1) Set the Failure Date to the day of birth in this year.    -   2) Set the status of an alert record to a new status (e.g., 10),        to indicate that this is not an active alert, but that it will        become active in the future (the day of birth).        For example, if a member will turn 50 between now and the end of        the measurement year, and had an FOBT 11 months ago, the Failure        Date would be the later of the 2 dates.        Failure Date should be set outside of the measurement year when        the failure date is calculated on an Alert which is currently        active and compliant, i.e. anniversary of colonoscopy is 10 yrs        in the future.        Failure Date should not be set outside of the measurement year        when the Failure Date is calculated on an Alert which is not        currently active, but will become active within the current        measurement year, i.e. member ages into eligibility or meets        coverage requirements within the measurement year.

If on a subsequent analysis a previously computed failure date should beupdated, this may be handled as follows:

-   -   1) Update existing, compliant and active (status=1) Alert        Summary record,        -   a. Failure Date can be overwritten with a date further out            into the future (i.e. no history of previous failure dates            retained).    -   2) Update Future Failure Date Alert Summary record (status=11)        -   a. Failure Date could be updated to a date further out into            the future if the alert is not yet active        -   b. When the alert becomes Active:            -   i. create a new Alert Summary record (status=1)            -   ii. retire the previous ‘future failure date’ record by                setting the status to 12        -   c. If the rule is turned off            -   i. retire the ‘future failure date’ with a status of 13                (analogous to normal alerts being retired with a status                of 3).

Determine whether the rule is age dependent. If it is not, check ifmember is compliant. If compliant, then compute a future failure date.If not compliant, the algorithm exits without an output.

If the rule is age dependent, the member is checked for age eligibility.If eligible, the member undergoes the compliance check as described inthe previous paragraph.

If the member does not pass the age eligibility check, the algorithmdetermines whether the member's birth date is between the run date andthe end of the measurement year. If it is, then the member is re-runwith a run date equal to the member's birth date and goes through ageeligibility check again. If the member fails the eligibility checkagain, the algorithm exits. If the member passes the age eligibilitythis time around, the member then goes through the compliance check. Theonly difference at this point between a member who was age eligible onthe original run date and a member who became age-eligible uponadvancing the run date is that non-compliance is of interest, in thatnon-compliance indicates aging in to the rule and that the member shouldbe flagged for possible intervention soon after the age-in failure date.As for a member who was aged into eligibility and who turns out to bealready compliant, a failure date is also calculated and stored.

Other considerations:

Members who were aged into eligibility should not be put into thedenominator tally. Members who were found to be compliant upon aging-inshould not be put into the numerator tally.

Other Failure Date Use Cases:

Osteoporosis

Once Eligibility is met (i.e. IESD can be determined), Failure Date isIESD+180 days

Coronary Artery Disease

Failure Date is anniversary of screening.

Diabetes

Diabetics require nephropathy screening within measurement year

Failure Date is one of:

-   -   end of next measurement year    -   anniversary of screening test

Rheumatoid Arthritis

Failure Date=end of next measurement year

Prevention and Screening

Failure Date is not-applicable.

Prevention and Screening

Failure Date is end of next measurement year.

-   -   E.g. November 15=special date because January 1 minus 45 day        gap.    -   When a ‘future failure date’ Alert Summary record becomes        ‘Active’, the system may ‘retire’ the future failure date' alert        with a special status (e.g., 11 ), and create a new alert record        as normal.

In the table below are listed HEDIS/STAR rules categories and failuredate scenarios that may be applied to a gap in care alert analysis.

LIST of HEDIS Star Rules for Failure Date

Standard Run Prospective Category HEDIS HEDIS SPEC Failure Date FailureDate Description ABBRV TEXT HEDIS Rule ID 1 Rule Description ScenariosScenarios Colorectal COL The percentage HEDIS 10594 Adults 50 to 75 1)Age In-DOB same Cancer of members star years of age who 2) 3 ClinicalScreening 50-75 years of have claims for Component- age who hadappropriate a. Fecal occult blood appropriate screening for test (FOBT)during the screening for colorectal cancer measurement year colorectalb. Flexible cancer. sigmoidoscopy during the measurement year or thefour years prior c. Colonoscopy during the measurement year or the nineyears prior to the measurement year 3) Eligibility Enrollment dateBreast Cancer BCS The percentage HEDIS 10595 Women 40 to 69 1) AgeIn-DOB same Screening of women 40- star years of age who 2) Clinical 69years of age had a claim for a Component-One or who had a mammogram tomore mammograms mammogram screen for breast during the to screen forcancer during the measurement year or breast cancer. measurement yearthe year prior to the or the year prior to measurement year themeasurement 3) Eligibility year Enrollment date Prevention GSO Thepercentage HEDIS 10596 Patients 65 years 1) Age In-DOB same andScreening of Medicare star and older, without a 2) Clinical members 65prior diagnosis of Component-One or years and older glaucoma or more eyeexams for who received a glaucoma suspect, glaucoma by an eye glaucomaeye who had a claim for care professional (i.e., exam by an eye aglaucoma eye ophthalmologist, care exam by an eye- optometrist) duringthe professional care professional measurement year or for early forearly the year prior to the identification identification of measurementyear. of glaucomatous 3) Eligibility glaucomatous conditions duringEnrollment date conditions. the measurement year or the year priorPrevention AAP The percentage HEDIS 10613 Patients 20 years 1) AgeIn-DOB same and Screening of members 20 star and older who had 2)Clinical years and older an ambulatory or Component-One or who had anpreventive care visit more ambulatory or ambulatory or in the past year-preventive care visits preventive care Medicare/Medicaid during thevisit. measurement year. 3) Eligibility Enrollment date Hypertension CBPHEDIS 10615 Patients 18-85 years N/A-based on lab N/A-based star of agewho had a value on lab value diagnosis of hypertension (HTN) and whoseBP was adequately controlled (<140/90) during the measurement year.Coronary CMC The percentage HEDIS 10617 Patients 18 to 75 1) Age In-DOBsame Artery of members star years of age who 2) Clinical Disease 18-75years of were discharged Component-An LDL- (CAD) age who were alive foracute C test performed discharged myocardial during the alive for AMI,infarction (AMI), measurement year, as coronary artery coronary arteryidentified by bypass bypass graft claim/encounter or graft (CABG) (CABG)or automated laboratory or percutaneous data. percutaneous transluminal3) Eligibility coronary coronary Enrollment date interventionsangioplasty (PTCA) (PCI) from in the past year or January 1- diagnosedwith November 1 of ischemic vascular the year prior disease (IVD) in theto past two years who the have claims for a measurement LDL Screeningyear, or who during the past 12 had a diagnosis months of ischemicvascular disease (IVD) during the measurement year and the year prior tothe measurement year, who had each of the following during themeasurement year. LDL-C screening Diabetes HEDIS 10620 Patients 18 to 75N/A-based on lab N/A-based star years of age with value on lab valuediabetes (type 1 and type 2) with the most recent HbA1c >9%. DiabetesCDC The percentage HEDIS 10621 Patients 18 to 75 1) Age In-DOB same ofmembers star with diabetes (type 2) Clinical 18-75 years of 1 and type2) who Component-An age with received HbAlc HbA1c test performeddiabetes (type Testing in the last during the 1 and type 2) yearmeasurement year, as who had identified by Hemoglobin claim/encounter orA1c (HbA1c) automated laboratory testing. data. 3) EligibilityEnrollment date Diabetes CDC The percentage HEDIS 10622 Patients 18 to75 1) Age In-DOB same of members star years of age with 2) Clinical18-75 years of diabetes (type 1 and Component-An LDL- age with type 2)who had an C test performed diabetes (type LDL-C screening during the 1and type 2) test performed in measurement year, as who had LDL- the past12 months identified by C screening. claim/encounter or automatedlaboratory data. 3) Eligibility Enrollment date Diabetes CDC HEDIS 10623Patients 8 to 75 N/A-based on lab N/A-based star years of age with valueon lab value diabetes (type 1 and type 2) who have claims for an LDL- Ctest done during the past 12 months and most recent LDL-C < 100 mg/dLDiabetes CDC The percentage HEDIS 10624 Patients 18 to 75 1) Age In-DOBsame of members star years of age with 2) Clinical 18-75 years ofdiabetes (type 1 and Component-A age with type 2) who have a nephropathyscreening diabetes (type claim for a diabetic test or evidence of 1 andtype 2) nephropathy nephropathy, as who had screening test or documentedthrough medical evidence of diabetic administrative data. attention fornephropathy 3) Eligibility nephropathy. documented in Enrollment dateclaims data in the measurement year Diabetes CDC The percentage HEDIS10625 Patients 18 to 75 1) Age In-DOB same of members star years of agewith 2) Clinical Component 18-75 years of diabetes (type 1 and An eyescreening for age with type 2) who have a diabetic retinal diseasediabetes (type claim for a retinal as identified by 1 and type 2) ordilated eye exam administrative data. who had eye by an eye care Thisexam (retinal) professional includes diabetics who performed.(optometrist or had one of the ophthalmologist) in following. themeasurement A retinal or dilated year or a negative eye exam by an eyeretinal exam (no care professional evidence of (optometrist orretinopathy) by an ophthalmologist) in the eye care measurement year, orprofessional A negative retinal documented in exam (no evidence ofclaims data in the retinopathy) by an eye year prior to the careprofessional measurement year in the year prior to the measurement year3) Eligibility Enrollment date **Note sure-can we tell in a claim ifnegative retinal exam? 30272 CAT2 code, can we produce failure date? yesOsteoporosis OMW The percentage HEDIS 10629 Women 67 years of 1) Age Insame of women 67 star age and older who 2) event based: years of agesuffered a fracture Appropriate testing or and older who and who hadeither treatment for suffered a a bone mineral osteoporosis after thefracture and density (BMD) test fracture defined by any who had eitheror prescription for a of the a bone mineral drug to treat or followingcriteria. density (BMD) prevent A BMD test (Table test or osteoporosisin the OMW-B) on the IESD prescription for six months after the or inthe 180-day (6- a drug to treat fracture. Sister rule month) periodafter or prevent of 10710 the IESD, or osteoporosis in A BMD test (Tablethe six months OMW-B) during the after the inpatient stay for thefracture. fracture (applies only to fractures requiringhospitalization), or A dispensed prescription (Table OMW-C) to treatosteoporosis on the IESD or in the 180-day (6-month) period after theIESD 3) Eligibility Enrollment date Rheumatoid ART The percentage HEDIS10630 Patients 18 years of 1) Age In-DOB same Arthritis of members starage and older who 2) Clinical who were were diagnosed Component-Membersdiagnosed with with rheumatoid who had at least one rheumatoid arthritisand who ambulatory arthritis and were dispensed at prescriptiondispensed who were least one for a DMARD during dispensed at ambulatorythe measurement year. least prescription for a 3) Eligibility oneambulatory disease modifying Enrollment date prescription foranti-rheumatic drug a disease (DMARD) modifying anti- rheumatic drug(DMARD). Geriatrics HEDIS 10638 Patients 65 years of N/A-No Failure dateN/A-based star age and older who possible on lab value had aprescription claim for at least one high risk medication per HEDIS listduring the measurement year Prevention PNU The percentage HEDIS 10707Members 65 years 1) Age In same and Screening of Medicare star of ageand older members 65 who have ever years of age received a and older asof pneumococcal January 1 of vaccination. the measurement year who haveever received a pneumococcal vaccine. Osteoporosis OMW HEDIS 10710 Women67 years of 1) Age In Not to be star age and older who 2) event based:IESD + used in suffered a fracture measurement prospective and who hadeither window-OSTEO FX + a bone mineral 6 mth density (BMD) test 3)Eligibility or prescription for a Enrollment date drug to treat orprevent osteoporosis in the 7 days after the fracture Prevention FSO Thepercentage HEDIS 10712 Members over 65 1) Age In and Screening ofMedicare star years old should 2) Clinical-Any time members 65 receive aflu shot in the flu season (need years of age after September 1st theexact dates) and older as of of the measurement January 1 of year. themeasurement year who received an influenza vaccination between September1 of the measurement year and the date when the Medicare CAHPS surveywas completed. Diabetes HEDIS 10763 Patients 18 to 75 N/A-based on labN/A-based star years of age with value on lab value diabetes (type 1 andtype 2) with the most recent HbA1c >9%. Sister rule of 10620 except nolonger requires lab. Diabetes HEDIS 10764 Patients 8 to 75 N/A-based onlab N/A-based star years of age with value on lab value diabetes (type 1and type 2) who have claims for an LDL- C test done during the past 12months and most recent LDL-C < 100 mg/dL. Sister rule of 10623 except nolonger requires lab. Prevention AAP The percentage HEDIS 10784 Patients20 years 1) Age In-DOB same and Screening of members 20 star and olderwho had 2) Clinical years and older an preventive care Component-One orwho had an visit in the past year more ambulatory or ambulatory orMedicare/ preventive care visits preventive care Medicaid (Table AAP-A)during visit. the measurement year. 3) Eligibility Enrollment datePrevention ABA The percentage HEDIS 10894 HEDIS measure for BMI duringthe and Screening of members star commercial, measurement year or 18-74years of Medicare and the year prior to the age who had an Medicaid.ABA- measurement year as outpatient visit Adult BMI documented throughand whose Assessment either administrative body mass data or medicalrecord index review. (BMI) was documented during the measurement year orthe year prior to the measurement year. Prevention COA The percentageHEDIS 10895 HEDIS measure for 1) Age In-DOB same and Screening of adults66 star Medicare SNP. 2) Clinical years and older COA-FunctionalComponent-At least who had Status Assessment one functional statusFunctional assessment during the Status measurement year Assessment(Table COA-D). 3) Eligibility Enrollment date Prevention COA Thepercentage HEDIS 10896 HEDIS measure for 1) Age In-DOB same andScreening of adults 66 star Medicare SNP. 2) Clinical years and olderCOA-Medication Component-At least who had Review one medication reviewMedication (Table COA-B) Review conducted by a prescribing practitioneror clinical pharmacist during the measurement year and the presence of amedication list in the medical record (Table COA-C), as documentedthrough administrative data. 3) Eligibility Enrollment date PreventionCOA The percentage HEDIS 10897 HEDIS measure for 1) Age In-DOB same andScreening of adults 66 star Medicare SNP. 2) Clinical years and olderCOA-Pain Component-At least who had Pain Screening one pain screening orScreening pain management plan during the measurement year. 3)Eligibility Enrollment date Chronic SPR HEDIS 10626 Patients 40 yearsof 1) Age In Obstructive non- age and older with a 2) event based:IESD + Pulmonary star new diagnosis of or measurement Disease newlyactive COPD window-Spiro FX + (COPD) (no prior claims in 6 mth the 2years prior to 3) Eligibility the diagnosis) who Enrollment date have aclaim for having received appropriate spirometry testing to confirm thediagnosis in the two years before to 180 days after the diagnosis.Sister rule of 10709

What is claimed is:
 1. A system comprising: a computer network forreceiving health insurance claims data; a database comprisingpredetermined medical treatment protocols for a plurality of medicalconditions; an electronic storage device comprising executable softwareinstructions; at least one processor in electronic communication withsaid computer network, said database, and the electronic storage device,wherein the executable software instructions, when executed, configurethe processor to analyze said health insurance claims data to identify atriggering event for an insured patient, determine a medical treatmentprotocol associated with the triggering event, establish a date for afollow-up event for said insured patient based at least in part on saidassociated medical treatment protocol, and generate a gap in care alertif subsequently gathered health insurance claims data does not containthe follow-up event by said date; and an alert delivery subsystemconfigured to deliver said alert electronically to a receiver.
 2. Thesystem of claim 1, wherein: said triggering event is a date when ahealthcare provider performs a medical procedure on said patient.
 3. Thesystem of claim 1, wherein: said processor is configured to generatesaid alert a number of days in advance of said date for the follow-upevent.
 4. The system of claim 1, wherein: said processor is configuredto generate said alert a number of days after said date for thefollow-up event.
 5. The system of claim 1, wherein: said medicaltreatment protocols includes recommended steps for medical treatment forparticular medical conditions.
 6. The system of claim 5, furthercomprising: additional executable software instructions, stored at saidelectronic storage device, which when executed, further configure theprocessor to receive health care provider prescribed steps, generate analert message if said prescribed steps do not match said recommendedsteps, and deliver said alert message by way of said alert deliverysubsystem.
 7. The system of claim 6, wherein: said alert messagecomprises a prompt for the health care provider to consider revising theprescribed steps to be consistent with the recommended steps.
 8. Thesystem of claim 1, wherein: said alert is automatically generated andautomatically sent to said receiver.
 9. The system of claim 8, wherein:said receiver is associated with an electronic medical record system foran insured patient.
 10. The system of claim 8, wherein: said receiver isa patient's personal mobile communications device and said alert is atext message.
 11. The system of claim 1, wherein: said medical treatmentprotocols include time periods associated with each recommended step.12. The system of claim 11, wherein: said time periods are determinedusing performance measure rules.
 13. The system of claim 12, wherein:said performance measure rules are selected from the group consistingof: HEDIS and STAR.
 14. The system of claim 1, wherein: said triggeringevents is determined using performance measure rules selected from thegroup consisting of: HEDIS and STAR.
 15. A system comprising: a computernetwork for receiving health insurance claims data from a number ofinsured members of a health insurance provider; a database comprisingpredetermined medical treatment protocols for a plurality of medicalconditions, wherein said medical treatment protocols compriserecommended treatment steps and associated time periods between each ofsaid treatment steps; an electronic storage device comprising executablesoftware instructions; at least one processor in electroniccommunication with said computer network, said database, and theelectronic storage device, wherein said executable softwareinstructions, when executed, configure the processor to analyze saidhealth insurance claims data to identify a triggering event for aninsured patient, determine the medical treatment protocol associatedwith the triggering event, determine one or more recommended treatmentsteps and associated follow-up dates, and generate a gap in care alertif subsequently gathered health insurance claims data for the insuredpatient does not contain the one or more recommended treatment steps bythe associated follow-up dates; and an alert delivery subsystemconfigured to deliver said gap in care alert electronically to areceiver, wherein said gap in care alert message comprises a prompt tofollow up with said health care provider for the recommended treatmentstep.
 16. The system of claim 15, further comprising: additionalsoftware instructions, which when executed, configure the at least oneprocessor to receive health care provider prescribed treatment steps,compare said prescribed steps to said recommended treatment steps, andgenerate a treatment advice message if said prescribed steps do notmatch said recommended treatment steps, wherein said treatment advicemessage comprises a prompt to consider revising the prescribed treatmentsteps to match the recommended treatment steps.
 17. The system of claim15, wherein: said follow-up dates are determined using performancemeasure rules selected from the group consisting of: HEDIS and STAR. 18.A system comprising: a computer network configured to receive healthinsurance claims data for a number of insured patients of a healthinsurance provider; a database comprising predetermined medicaltreatment protocols for a plurality of medical conditions, wherein saidmedical treatment protocols comprise recommended treatment steps andassociated time periods for medical treatment follow-up for particularmedical conditions; an electronic storage device comprising softwareinstructions; a gap in care alert module comprising at least onecomputer processor in electronic communication with said computernetwork, said database, and said electronic storage device, wherein saidsoftware instructions, when executed, configure said at least onecomputer processor to analyze said received health insurance claims datato identify a triggering event for an insured patient, identify amedical treatment protocol associated with said triggering event,determine an expected date for a follow-up event by retrieving the timeperiod associated with the next recommended treatment step of theidentified medical treatment protocol and adding the time period and agrace period to the triggering event, and automatically generating a gapin care alert if subsequently gathered health insurance claims data doesnot indicate that medical treatment follow-up has occurred for saidpatient by said expected date; and a treatment advice module comprisingat least one computer processor in electronic communication with saidcomputer network, said database, and the electronic storage device,wherein software instructions, when executed, further configure said atleast one computer processor to retrieve recommended treatment stepsassociated with said identified medical treatment protocol and generatea message to the health care provider if subsequently gathered healthinsurance claims data does not indicate that the health care providerstreatment steps do not match the recommended treatment steps, whereinthe generated message comprises a prompt for the health care provider toconsider performing the recommended treatment steps.
 19. The system ofclaim 18, wherein: said electronic storage device comprises additionalsoftware instructions, which when executed, cause said at least onecomputer processor to determine an early warning date by subtracting apredetermined number of days from the expected date for a follow-upevent for said insured patient, and automatically generate anapproaching gap in care alert if subsequently gathered health insuranceclaims data does not indicate that medical follow-up has occurred forsaid patient by said early warning date.
 20. The system of claim 18,wherein: said triggering event is a date when a healthcare providerperforms a medical procedure on said insured patient.